Artificial Intelligence In Drug Discovery and Screening Market Research Report - Segmented By Application (Drug Optimization & Repurposing, Preclinical Testing), By Therapeutic Area (Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases, Infectious Diseases, Others) and Region - Size, Share, Growth Analysis | Forecast (2024 2030)

Market Size and Overview:

The global market for artificial intelligence in drug discovery and screening achieved a valuation of USD 364.67 million and is anticipated to attain a market size of USD 4000.56 million by the culmination of 2030. Projected to exhibit a Compound Annual Growth Rate (CAGR) of 40.8% over the forecast span from 2024 to 2030, the market's advancement is propelled by factors such as the escalating count of cross-industry collaborations and alliances.

Market Overview:

Artificial intelligence, a subfield of computer science focused on emulating intelligent behavior, empowers computers to emulate human and animal-like thinking and execution of tasks, incorporating learning from errors. Designed as algorithms to enable effective task execution with minimal errors, artificial intelligence applies deep learning and machine learning methodologies to imbue computers with personified knowledge for multifarious activities.

In the domain of drug development, artificial intelligence finds diverse applications encompassing disease tracking, formulation of remedies, and prediction of mutating animal viruses. Its pivotal role in enhancing Research and Development (R&D) for medication discovery has been demonstrated in aiding researchers to develop remedies for chronic diseases.

Drug discovery and development, integral processes in medicine, pharmacology, and biotechnology, entail the identification of a biological target such as an enzyme protein, gene, or receptor, followed by the design, development, and procurement of a drug. Unlike traditional methods where medications were identified by determining active ingredients, contemporary drug discovery evaluates pharmaceuticals based on new criteria encompassing bioavailability, effectiveness, potency, and toxicity.

Artificial intelligence is extensively harnessed in the healthcare sector, particularly in the exploration of novel medications. It contributes to the identification of therapeutic targets and plays a vital role in swiftly identifying, producing, detecting, and screening small compounds. The market is poised for exponential growth due to the advantages of employing advanced techniques over traditional procedures, further bolstered by increasing industry alliances and partnerships. The cost and time efficiency brought about by artificial intelligence in the drug discovery process are significant catalysts for market expansion. Nevertheless, the dearth of skilled professionals and datasets in the realm of drug discovery poses a challenge to market growth. Conversely, heightened awareness of artificial intelligence is expected to yield substantial benefits for manufacturers in the artificial intelligence for medication discovery and development market.

Impact of COVID-19 on the AI Drug Discovery & Screening Market:

The ongoing COVID-19 pandemic has strained existing healthcare systems, fostering demand for new medicine solutions. In response, pharmaceutical companies have increasingly turned to AI-powered solutions in clinical trials, expediting drug development during and post the pandemic.

The pandemic has reshaped the pharmaceutical industry landscape, resulting in significant repercussions across the entire innovation and manufacturing value chain. Patent filings have notably decreased during the epidemic, leading to a substantial reduction in industry revenue and overall workforce.

MARKET DRIVERS:

An increase in the number of cancer and other disease cases is estimated to boost the market growth.

The market is anticipated to experience growth driven by an escalation in the number of cancer and other disease cases. Cancer, presently a leading cause of global mortality, underscores the potential of Artificial Intelligence (AI) in comprehending the mechanisms through which cancer cells develop resistance to anticancer treatments. This understanding facilitates the creation and development of medications tailored to the market's needs. Additionally, the substantial demand for effective treatments for severe cancers contributes significantly to the burgeoning role of AI in drug discovery.

Increased AI research and development activities are propelling market growth.

The surge in research and development activities related to AI is a pivotal driver propelling market growth. The flourishing market for AI in drug research and development owes its momentum to increased collaborations and cross-industry alliances. The indispensability of AI in medication discovery, coupled with substantial investments in AI research and development, is expected to fuel the expansion of the market. Rising awareness of artificial intelligence, particularly in burgeoning markets such as China and India, further adds to the escalating demand in the market.

MARKET RESTRAINTS:

Market expansion in low-income countries is hampered by a lack of advanced instruments.

The expansion of the market in low-income countries encounters hindrances due to the lack of advanced instruments. The vast data sets available for drug development in pharmaceutical corporations, containing millions of chemicals, may pose challenges for artificial intelligence techniques. This limitation is forecasted to impede the growth of AI in the drug discovery sector, particularly in regions with lower economic capacities.

The expensive cost of AI integration is limiting market expansion.

The prohibitive cost associated with the integration of AI serves as a constraint on market expansion. The drug development market for artificial intelligence faces challenges stemming from high technology costs and technological constraints. Throughout the projection period spanning 2023 to 2030, a shortage of skilled professionals and a lack of awareness are poised to act as additional restraints, decelerating the pace of market growth.

This research report based on AI Drug Discovery & Screening Market is segmented and sub-segmented by application, Therapeutics, and region.

AI Drug Discovery & Screening by Application:

• Drug Optimization & Repurposing
• Preclinical Testing
• Other

In 2021, the segment focused on Drug Optimization & Repurposing claimed the highest revenue share, accounting for nearly 50.0 percent based on application. Advanced AI systems, such as Deep Learning (DL) and drug modeling, are employed in this segment to assess undesirable drug effects and overall drug efficacy. The pharmaceutical industry strategically utilizes AI technology to enhance existing pharmaceuticals, repurposing them for different indications, thereby reducing development costs and achieving increased overall efficacy.

Another burgeoning application of AI in drug development is Preclinical Testing. AI algorithms and associated technologies significantly expedite the selection of individuals for clinical trials based on their medical history and suitability, consequently reducing the overall clinical timeline. Predictive machine learning algorithms, grounded in genome-specific data, aid in identifying lead compounds and patient populations. Companies like Amplion leverage AI technology to meticulously select biomarkers, streamline patient recruitment, and optimize biomarker selection, thereby diminishing clinical study timelines.

AI Drug Discovery & Screening by Therapeutics:

• Oncology
• Neurodegenerative Diseases
• Cardiovascular Diseases
• Metabolic Diseases
• Infectious Diseases
• Others

In 2021, the oncology sub-segment dominated with a revenue share exceeding 20.0 percent. AI systems play a crucial role in early disease detection, addressing the commonality of human error in disease diagnosis. The increasing accuracy of AI in disease detection, exemplified by a Northwestern University researcher accurately identifying lung cancer in scans that radiologists might have overlooked, underscores the potential of AI to facilitate earlier disease identification. AI, integrated with genetic sequences and patient histories, allows for personalized treatments based on individualized needs.

From 2023 to 2030, the Infectious Diseases category is anticipated to be the fastest-growing application segment. AI, in conjunction with platforms like the Internet of Things (IoT), is deployed to enhance understanding of infectious diseases, including their transmission, infection mechanisms, and vaccine development. Networked devices, such as smartphones and medical devices, collect data that aids in comprehending lifestyle trends, anomalies, and disease research. The current global scenario underscores the increasing importance of developing strategies for detecting infectious diseases.

AI Drug Discovery & Screening by Region:

• North America
• Europe
• Asia-Pacific
• Latin America
• The Middle East and Africa

In 2021, North America claimed the highest revenue share, surpassing 55.0 percent. The United States, a pioneer in AI technology, has integrated AI across various industries, including pharmaceuticals. Major American IT companies collaborate with esteemed institutes to accelerate medication discovery, design, and repurposing. The application of AI in researching diseases and deriving valuable conclusions for disease management is widespread.

From 2023 to 2030, the Asia-Pacific (APAC) market is projected to experience the fastest growth. Developing countries in the APAC region are increasingly leveraging AI to enhance disease understanding and drug research. Noteworthy collaborations, such as that between Intuition Systems in India and Lantern Pharma for medication discovery and biomarker identification, exemplify the region's commitment to advancing healthcare through AI. Other AI firms like Niramai and Sigtuple contribute to healthcare improvements by expediting drug research and enhancing the identification of target proteins and biomarkers.

AI Drug Discovery & Screening by Company:

The urgency to expedite drug development for improved treatments is driving the adoption of Artificial Intelligence (AI) in the pharmaceutical industry. Leading IT companies are intensifying their efforts to accelerate medication discovery, with global market dominance held by corporations such as IBM, Microsoft, Atomwise Inc., Cloud Pharmaceuticals, Benevolent AI, and BIO AGE. Collaborations between technology firms and academic/research institutions play a pivotal role in fostering AI adoption across the pharmaceutical industry, facilitating the development of pharmaceuticals with reduced adverse effects and expediting comprehensive disease research.

Key competitors in the worldwide artificial intelligence in drug development industry include IBM Watson, Exscientia, GNS Healthcare, Alphabet (DeepMind), Benevolent AI, BioSymetrics, Euretos, Berg Health, Atomwise Intro, Cyclica, among others.

Recent Developments in the AI Drug Discovery & Screening Market:

• Product Launch:

In December 2021, Insilico Medicine, an AI-driven medication development company, announced the dosing of the first healthy volunteer in a microdose trial of ISM 001-005. This small-molecule inhibitor of a biological target, discovered by Pharma.AI and designed with AI, is currently undergoing trials in Australia.

In July 2021, Chief.AI, a machine learning platform, introduced a pay-as-you-go AI platform for drug discovery. This platform provides Small and Medium-sized Enterprises (SMEs) with cost-effective access to advanced technology, reducing the trial-and-error aspect of drug development and enabling faster, more precise identification of breakthrough therapies.

• Collaborations:

In July 2021, Sanofi, the Paris-based pharmaceutical giant, entered into a research agreement with Exscientia, a company utilizing AI to discover novel medication candidates. The collaboration, potentially valued at up to $5.2 billion, signifies a milestone for AI-based drug discovery approaches. Despite attracting substantial investments, these approaches, promising more efficient and risk-free discovery of novel medications, have yet to fully materialize.